code: def read_tfrecord_dataset(self, filenames, ep):
      # Read the dataset at `filenames` into a tf.data.Dataset and returns the
      # number of time-steps (just the number of records in the dataset) and the
      # number of trajectories.
  
      last_timestep = -1
      num_time_steps = 0
      num_trajectories = 0
      for ex in generator_utils.tfrecord_iterator(
          filenames, example_spec=ep.example_reading_spec()[0]
      ):
          num_time_steps += 1
          this_timestep = ex[env_problem.TIMESTEP_FIELD][0]
          if 1 + last_timestep != this_timestep:
              num_trajectories += 1
              self.assertEqual(0, this_timestep)
          last_timestep = this_timestep
      num_trajectories += 1
  
      return num_trajectories, num_time_steps
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import gym
  from gym.spaces import Box
  from gym.spaces import Discrete
  import numpy
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.envs import env_problem
  from tensor2tensor.envs import env_problem_utils
  from tensor2tensor.envs import gym_env_problem
  from tensor2tensor.layers import modalities
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 7 for calling the GymEnvProblemTest obj's underlying member method code with example usage: obj.read_tfrecord_dataset(filenames, ep) and returns: num_trajectories,  num_time_steps